This notebook contains a set of analyses for analyzing GOBbluth89’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
GOBbluth89 | training | published before 2020 | 74 | 0 |
GOBbluth89 | validation | published 2020 | 12 | 0 |
GOBbluth89 | test | published after 2020 | 4 | 0 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
GOBbluth89 | Fantasy Flight Games | 32.4% | 1.1% | 30.18 |
GOBbluth89 | CMON Global Limited | 5.4% | 0.4% | 15.23 |
GOBbluth89 | Space Cowboys | 2.7% | 0.2% | 13.67 |
GOBbluth89 | Asmodee | 31.1% | 2.5% | 12.26 |
GOBbluth89 | Race | 10.8% | 1.0% | 11.11 |
GOBbluth89 | Collectible Components | 17.6% | 1.7% | 10.19 |
GOBbluth89 | Alderac Entertainment Group | 5.4% | 0.7% | 7.25 |
GOBbluth89 | Artist Klemens Franz | 4.1% | 0.6% | 6.66 |
GOBbluth89 | ZMan Games | 9.5% | 1.4% | 6.59 |
GOBbluth89 | Dice With Icons | 6.8% | 1.1% | 6.20 |
GOBbluth89 | Pegasus Spiele | 12.2% | 2.2% | 5.54 |
GOBbluth89 | Mayfair Games | 5.4% | 1.1% | 4.82 |
GOBbluth89 | Bluffing | 23.0% | 5.7% | 4.03 |
GOBbluth89 | Acting | 4.1% | 1.2% | 3.39 |
GOBbluth89 | Hand Management | 55.4% | 20.1% | 2.76 |
GOBbluth89 | Party Game | 13.5% | 9.3% | 1.45 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2012 | 124742 | Android: Netrunner | 0.980 | yes |
2 | 2017 | 233078 | Twilight Imperium: Fourth Edition | 0.957 | yes |
3 | 2016 | 205637 | Arkham Horror: The Card Game | 0.913 | yes |
4 | 2016 | 187645 | Star Wars: Rebellion | 0.864 | no |
5 | 2018 | 205896 | Rising Sun | 0.838 | no |
6 | 2019 | 281946 | Aftermath | 0.760 | no |
7 | 2010 | 73171 | Earth Reborn | 0.702 | no |
8 | 2008 | 37111 | Battlestar Galactica: The Board Game | 0.679 | no |
9 | 2015 | 169255 | A Game of Thrones: The Card Game (Second Edition) | 0.666 | yes |
10 | 2019 | 285774 | Marvel Champions: The Card Game | 0.643 | yes |
11 | 2018 | 244711 | Newton | 0.621 | no |
12 | 2018 | 257501 | KeyForge: Call of the Archons | 0.581 | yes |
13 | 2017 | 221107 | Pandemic Legacy: Season 2 | 0.576 | no |
14 | 2010 | 68182 | Isla Dorada | 0.519 | no |
15 | 2016 | 205359 | Star Wars: Destiny | 0.519 | yes |
16 | 2012 | 104162 | Descent: Journeys in the Dark (Second Edition) | 0.499 | no |
17 | 2018 | 313010 | Cosmic Encounter: 42nd Anniversary Edition | 0.497 | no |
18 | 2018 | 252328 | Star Wars: X-Wing (Second Edition) | 0.494 | yes |
19 | 2008 | 38453 | Space Alert | 0.477 | no |
20 | 2012 | 129622 | Love Letter | 0.459 | yes |
21 | 2017 | 232918 | Fallout | 0.438 | no |
22 | 2018 | 257499 | Arkham Horror (Third Edition) | 0.396 | no |
23 | 2017 | 184151 | Legend of the Five Rings: The Card Game | 0.386 | no |
24 | 2017 | 174430 | Gloomhaven | 0.359 | yes |
25 | 2003 | 6472 | A Game of Thrones | 0.344 | no |
26 | 2011 | 96848 | Mage Knight Board Game | 0.339 | no |
27 | 2005 | 18723 | Aye, Dark Overlord! The Red Box | 0.334 | no |
28 | 2014 | 148228 | Splendor | 0.329 | no |
29 | 2010 | 25292 | Merchants & Marauders | 0.327 | no |
30 | 2019 | 283863 | The Magnificent | 0.295 | no |
31 | 2019 | 272453 | KeyForge: Age of Ascension | 0.280 | no |
32 | 2016 | 176083 | Hit Z Road | 0.273 | no |
33 | 2008 | 39463 | Cosmic Encounter | 0.271 | yes |
34 | 2011 | 59959 | Letters from Whitechapel | 0.269 | no |
35 | 2008 | 22826 | Mutant Chronicles Collectible Miniatures Game | 0.265 | no |
36 | 2011 | 77423 | The Lord of the Rings: The Card Game | 0.261 | yes |
37 | 2012 | 104363 | Rex: Final Days of an Empire | 0.256 | no |
38 | 2012 | 103885 | Star Wars: X-Wing Miniatures Game | 0.255 | yes |
39 | 2010 | 77130 | Sid Meier's Civilization: The Board Game | 0.255 | no |
40 | 2019 | 269385 | The Lord of the Rings: Journeys in Middle-Earth | 0.234 | no |
41 | 1997 | 42 | Tigris & Euphrates | 0.234 | no |
42 | 2004 | 9609 | War of the Ring | 0.231 | no |
43 | 2001 | 1345 | Genoa | 0.227 | no |
44 | 2015 | 183562 | Star Wars: X-Wing Miniatures Game – The Force Awakens Core Set | 0.223 | no |
45 | 2016 | 205059 | Mansions of Madness: Second Edition | 0.214 | no |
46 | 2018 | 246297 | Shadows: Amsterdam | 0.205 | no |
47 | 2009 | 45134 | Arcana | 0.202 | no |
48 | 2008 | 40270 | Call of Cthulhu: The Card Game | 0.201 | no |
49 | 2002 | 4286 | A Game of Thrones Collectible Card Game | 0.199 | no |
50 | 2015 | 181530 | Runebound (Third Edition) | 0.196 | no |
51 | 2019 | 286096 | Tapestry | 0.196 | no |
52 | 2015 | 175878 | 504 | 0.189 | no |
53 | 2019 | 266507 | Clank!: Legacy – Acquisitions Incorporated | 0.187 | no |
54 | 2017 | 234487 | Altiplano | 0.184 | no |
55 | 2008 | 33107 | Senji | 0.179 | no |
56 | 2005 | 18833 | Lord of the Rings: The Confrontation | 0.179 | no |
57 | 2019 | 270971 | Era: Medieval Age | 0.177 | no |
58 | 2013 | 146021 | Eldritch Horror | 0.171 | no |
59 | 2012 | 85394 | The Last Banquet | 0.169 | no |
60 | 2018 | 256226 | Azul: Stained Glass of Sintra | 0.164 | no |
61 | 2009 | 43111 | Chaos in the Old World | 0.161 | no |
62 | 2002 | 4390 | Carcassonne: Hunters and Gatherers | 0.160 | no |
63 | 2016 | 204837 | Game of Thrones: The Iron Throne | 0.157 | no |
64 | 2013 | 127024 | Room 25 | 0.156 | no |
65 | 2019 | 244099 | Herbaceous Sprouts | 0.156 | no |
66 | 2008 | 39953 | A Game of Thrones: The Card Game | 0.156 | no |
67 | 2015 | 175155 | Forbidden Stars | 0.153 | yes |
68 | 2011 | 103343 | A Game of Thrones: The Board Game (Second Edition) | 0.151 | yes |
69 | 2016 | 184919 | Greedy Greedy Goblins | 0.147 | no |
70 | 2016 | 205158 | Codenames: Deep Undercover | 0.147 | no |
71 | 2007 | 30539 | Get Bit! | 0.143 | no |
72 | 2001 | 5791 | Maelstrom | 0.140 | no |
73 | 2000 | 26055 | Twilight Imperium: Second Edition | 0.140 | no |
74 | 2009 | 47185 | Warhammer: Invasion | 0.140 | no |
75 | 2009 | 58798 | Cardcassonne | 0.140 | no |
76 | 2017 | 220775 | Codenames: Disney – Family Edition | 0.140 | no |
77 | 2016 | 205716 | New Angeles | 0.139 | no |
78 | 2019 | 271896 | Star Wars: Outer Rim | 0.137 | yes |
79 | 2011 | 83330 | Mansions of Madness | 0.136 | no |
80 | 2013 | 146278 | Tash-Kalar: Arena of Legends | 0.136 | no |
81 | 2000 | 478 | Citadels | 0.134 | no |
82 | 2010 | 71721 | Space Hulk: Death Angel – The Card Game | 0.131 | no |
83 | 2009 | 31563 | Middle-Earth Quest | 0.130 | no |
84 | 2005 | 12493 | Twilight Imperium: Third Edition | 0.129 | yes |
85 | 2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.126 | no |
86 | 2017 | 221805 | Breaking Bad: The Board Game | 0.126 | no |
87 | 2014 | 151369 | Illegal | 0.124 | no |
88 | 2018 | 259970 | The Lord of the Rings: The Card Game – Two-Player Limited Edition Starter | 0.123 | no |
89 | 2017 | 195539 | The Godfather: Corleone's Empire | 0.119 | no |
90 | 2004 | 9220 | Saboteur | 0.119 | no |
91 | 2014 | 164153 | Star Wars: Imperial Assault | 0.115 | yes |
92 | 2012 | 123096 | Space Cadets | 0.113 | no |
93 | 2009 | 43868 | The Adventurers: The Temple of Chac | 0.111 | no |
94 | 1995 | 112 | Condottiere | 0.110 | no |
95 | 2007 | 22825 | Tide of Iron | 0.110 | no |
96 | 2007 | 22827 | StarCraft: The Board Game | 0.109 | no |
97 | 2004 | 10547 | Betrayal at House on the Hill | 0.109 | no |
98 | 2012 | 103886 | Star Wars: The Card Game | 0.107 | yes |
99 | 1995 | 13 | Catan | 0.106 | yes |
100 | 2006 | 14808 | Marvel Heroes | 0.105 | no |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.92 |
Decision Tree | roc_auc | binary | 0.61 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think GOBbluth89 is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2016 | 187645 | Star Wars: Rebellion | 0.864 | no |
2018 | 205896 | Rising Sun | 0.838 | no |
2019 | 281946 | Aftermath | 0.760 | no |
2010 | 73171 | Earth Reborn | 0.702 | no |
2008 | 37111 | Battlestar Galactica: The Board Game | 0.679 | no |
What games does the model think GOBbluth89 is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
1876 | 521 | Crokinole | 0.000 | yes |
2019 | 247367 | Air, Land & Sea | 0.001 | yes |
2019 | 281073 | Cat Lady: Premium Edition | 0.001 | yes |
2000 | 822 | Carcassonne | 0.001 | yes |
2018 | 244228 | Reef | 0.001 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Android: Netrunner | Eldritch Horror | Splendor | A Game of Thrones: The Card Game (Second Edition) | Arkham Horror: The Card Game | Twilight Imperium: Fourth Edition | Rising Sun | Aftermath |
2 | Descent: Journeys in the Dark (Second Edition) | Room 25 | Illegal | Star Wars: X-Wing Miniatures Game – The Force Awakens Core Set | Star Wars: Rebellion | Pandemic Legacy: Season 2 | Newton | Marvel Champions: The Card Game |
3 | Love Letter | Tash-Kalar: Arena of Legends | Star Wars: Imperial Assault | Runebound (Third Edition) | Star Wars: Destiny | Fallout | KeyForge: Call of the Archons | The Magnificent |
4 | Rex: Final Days of an Empire | BANG! The Dice Game | Lost Legacy: The Starship | 504 | Hit Z Road | Legend of the Five Rings: The Card Game | Cosmic Encounter: 42nd Anniversary Edition | KeyForge: Age of Ascension |
5 | Star Wars: X-Wing Miniatures Game | Glass Road | Warhammer 40,000: Conquest | Forbidden Stars | Mansions of Madness: Second Edition | Gloomhaven | Star Wars: X-Wing (Second Edition) | The Lord of the Rings: Journeys in Middle-Earth |
6 | The Last Banquet | Lewis & Clark: The Expedition | King of New York | Zaginione Dziedzictwo: Gwiezdne Ostrze | Game of Thrones: The Iron Throne | Altiplano | Arkham Horror (Third Edition) | Tapestry |
7 | Space Cadets | Pelican Bay | DungeonQuest Revised Edition | Blood Rage | Greedy Greedy Goblins | Codenames: Disney – Family Edition | Shadows: Amsterdam | Clank!: Legacy – Acquisitions Incorporated |
8 | Star Wars: The Card Game | Impulse | Patchwork | Love Letter: The Hobbit – The Battle of the Five Armies | Codenames: Deep Undercover | Breaking Bad: The Board Game | Azul: Stained Glass of Sintra | Era: Medieval Age |
9 | Sky Tango | Warhammer: Diskwars | Arcadia Quest | Watson & Holmes | New Angeles | The Godfather: Corleone's Empire | The Lord of the Rings: The Card Game – Two-Player Limited Edition Starter | Herbaceous Sprouts |
10 | Robinson Crusoe: Adventures on the Cursed Island | Gunrunners | Spyfall | Pandemic Legacy: Season 1 | Lost Legacy: Fourth Chronicle – The Werewolf & Undying Heart | Sherlock Holmes Consulting Detective: Carlton House & Queen's Park | Pandemic: Fall of Rome | Star Wars: Outer Rim |
11 | Cockroach Poker Royal | Dungeon Twister: The Card Game | One Night Ultimate Werewolf | Biblios Dice | Sherlock Holmes Consulting Detective: Jack the Ripper & West End Adventures | Pandemic: Rising Tide | Neon Gods | Slyville |
12 | Mice and Mystics | Crossing | Pandemic: The Cure | Grand Austria Hotel | Agricola (Revised Edition) | Codenames: Duet | Cosmic Run: Regeneration | Living Planet |
13 | Scripts and Scribes: The Dice Game | Carcassonne: South Seas | Deception: Murder in Hong Kong | Star Wars: Armada | Pandemic: Reign of Cthulhu | Spirit Island | Everdell | Black Angel |
14 | Mafia: Vendetta | Rococo | Ultimate Werewolf | Lost Legacy: Second Chronicle – Vorpal Sword & Whitegold Spire | Love Letter Premium | This War of Mine: The Board Game | Coimbra | Last Bastion |
15 | Wiz-War (Eighth Edition) | Canalis | Three Kingdoms Redux | Love Letter: Batman | Black Orchestra | Whitehall Mystery | The World of SMOG: Rise of Moloch | Watergate |
16 | Merchant of Venus (Second Edition) | BattleLore: Second Edition | Sheriff of Nottingham | Die Fiesen 7 | Terraforming Mars | Massive Darkness | Heroes of Terrinoth | Tiny Towns |
17 | Zombicide | Ghost Blitz: 5 to 12 | Lost Legacy: Flying Garden | One Night Revolution | Krosmaster Arena 2.0 | Summit: The Board Game | The Binding of Isaac: Four Souls | TIME Stories Revolution: Damien 1958 NT |
18 | Il Vecchio | Sail to India | Akrotiri | One Night Ultimate Vampire | Unicornus Knights | Unlock!: Escape Adventures – Fifth Avenue | Concordia Venus | Century: A New World |
19 | Clash of Cultures | The Doom That Came to Atlantic City | Castles of Mad King Ludwig | Salem 1692 | The Butterfly Garden | Downforce | Fireball Island: The Curse of Vul-Kar | Cthulhu: Death May Die |
20 | Zug um Zug: Deutschland | Capo Dei Capi | Five Tribes | Mombasa | Flamme Rouge | SpyNet | One Week Ultimate Werewolf | Zombicide: Invader |
21 | Keyflower | Euphoria: Build a Better Dystopia | HINT | Yashima: Legend of the Kami Masters | Bloodborne: The Card Game | Codenames: Marvel | Les Aventuriers du Rail Express | KeyForge: Worlds Collide |
22 | Archipelago | Kampen om Fredriksten | Grog Island | OctoDice | Dead of Winter: The Long Night | Crossfire | Ticket to Ride: New York | Tainted Grail: The Fall of Avalon |
23 | Kemet | Caverna: The Cave Farmers | Orléans | The Grizzled | DOOM: The Board Game | Dragon Castle | A Song of Ice & Fire: Tabletop Miniatures Game – Stark vs Lannister Starter Set | Machi Koro Legacy |
24 | Smash Up | Rory's Story Cubes: Prehistoria | Black Fleet | T.I.M.E Stories | Turin Market | Legacy of Dragonholt | Root | Pandemic: Rapid Response |
25 | The Hobbit Card Game | City of Remnants | Sons of Anarchy: Men of Mayhem | Drakon (Fourth Edition) | Pandemic: Iberia | Unlock!: Escape Adventures – Temple of Ra | Treasure Island | Unlock!: Exotic Adventures – Expedition: Challenger |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
GOBbluth89 | owned | validation | GLM | roc_auc | 0.902 |
GOBbluth89 | owned | validation | Decision Tree | roc_auc | 0.498 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 298572 | Cosmic Encounter Duel | 0.364 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.220 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.151 | yes |
2020 | 304285 | Infinity Gauntlet: A Love Letter Game | 0.095 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.080 | no |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.073 | no |
2020 | 256940 | Krosmaster: Blast | 0.057 | no |
2020 | 301607 | KeyForge: Mass Mutation | 0.047 | no |
2020 | 294484 | Unmatched: Cobble & Fog | 0.043 | yes |
2020 | 315060 | Unmatched: Buffy the Vampire Slayer | 0.039 | yes |
2020 | 300322 | Hallertau | 0.039 | no |
2020 | 256317 | Guild Master | 0.037 | no |
2020 | 301716 | Glasgow | 0.034 | no |
2020 | 325635 | Unmatched: Little Red Riding Hood vs. Beowulf | 0.033 | yes |
2020 | 302425 | Unlock!: Mythic Adventures | 0.031 | no |
2020 | 298638 | Sheriff of Nottingham: 2nd Edition | 0.030 | no |
2020 | 284777 | Unmatched: Jurassic Park – InGen vs Raptors | 0.030 | no |
2020 | 271524 | TIME Stories Revolution: A Midsummer Night | 0.029 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.028 | no |
2020 | 296345 | Sherlock Holmes Consulting Detective: The Baker Street Irregulars | 0.028 | no |
2020 | 299607 | Capital Lux 2: Generations | 0.028 | no |
2020 | 287742 | TIME Stories Revolution: The Hadal Project | 0.027 | no |
2020 | 296892 | Sacred Rites | 0.025 | no |
2020 | 246900 | Eclipse: Second Dawn for the Galaxy | 0.024 | no |
2020 | 312267 | Star Wars: Unlock! | 0.024 | no |
2020 | 293296 | Splendor: Marvel | 0.023 | no |
2020 | 301880 | Raiders of Scythia | 0.023 | no |
2020 | 293889 | Fallout Shelter: The Board Game | 0.022 | no |
2020 | 299179 | Chancellorsville 1863 | 0.022 | no |
2020 | 184267 | On Mars | 0.022 | no |
2020 | 256999 | Project: ELITE | 0.021 | no |
2020 | 318084 | Furnace | 0.021 | no |
2020 | 327913 | Unlock!: Timeless Adventures – Arsène Lupin und der große weiße Diamant | 0.020 | no |
2020 | 302809 | Betrayal at Mystery Mansion | 0.020 | no |
2020 | 317105 | Tiny Epic Galaxies BLAST OFF! | 0.020 | no |
2020 | 293141 | King of Tokyo: Dark Edition | 0.018 | no |
2020 | 309113 | Ticket to Ride: Amsterdam | 0.018 | no |
2020 | 297030 | Tekhenu: Obelisk of the Sun | 0.018 | no |
2020 | 261403 | Inhuman Conditions | 0.017 | no |
2020 | 298047 | Marvel United | 0.016 | no |
2020 | 301767 | Mysterium Park | 0.016 | no |
2020 | 308652 | Age of Dogfights: WW1 | 0.016 | no |
2020 | 302723 | Forgotten Waters | 0.015 | no |
2020 | 245658 | Unicorn Fever | 0.015 | no |
2020 | 282922 | Windward | 0.015 | no |
2020 | 299592 | Beez | 0.015 | no |
2020 | 308416 | Tapeworm | 0.015 | no |
2020 | 233262 | Tidal Blades: Heroes of the Reef | 0.015 | no |
2020 | 287033 | Gray Eminence | 0.015 | no |
2020 | 295905 | Cosmic Frog | 0.014 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Published | ID | Name | Pr(Owned) | Owned |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.768 | no |
2022 | 331106 | The Witcher: Old World | 0.713 | no |
2021 | 340466 | Unfathomable | 0.351 | yes |
2021 | 285967 | Ankh: Gods of Egypt | 0.287 | no |
2022 | 335764 | Unmatched: Battle of Legends, Volume Two | 0.257 | no |
2021 | 256680 | Return to Dark Tower | 0.192 | no |
2021 | 343905 | Boonlake | 0.134 | no |
2021 | 339906 | The Hunger | 0.128 | no |
2021 | 298069 | Cubitos | 0.102 | no |
2021 | 333553 | For the King (and Me) | 0.090 | no |
2021 | 291847 | Mantis Falls | 0.088 | no |
2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.088 | no |
2021 | 340677 | Bad Company | 0.081 | no |
2021 | 324242 | Sheepy Time | 0.076 | no |
2021 | 339905 | Love Letter: Princess Princess Ever After | 0.067 | no |
2021 | 337397 | Warhammer Underworlds: Two-Player Starter Set | 0.062 | no |
2021 | 273330 | Bloodborne: The Board Game | 0.058 | no |
2022 | 317511 | Tindaya | 0.053 | no |
2021 | 295947 | Cascadia | 0.051 | no |
2022 | 295770 | Frosthaven | 0.049 | no |
2021 | 348461 | Castle Break | 0.048 | no |
2021 | 316080 | KeyForge: Dark Tidings | 0.047 | no |
2021 | 291572 | Oath: Chronicles of Empire and Exile | 0.045 | no |
2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.041 | no |
2022 | 346199 | A Game of Thrones: B'Twixt | 0.040 | no |
2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 0.040 | no |
2022 | 283137 | Human Punishment: The Beginning | 0.039 | no |
2021 | 341169 | Great Western Trail (Second Edition) | 0.039 | no |
2021 | 294986 | Necromolds: Monster Battles | 0.037 | no |
2021 | 308989 | Bristol 1350 | 0.034 | no |
2022 | 322524 | Bardsung | 0.032 | no |
2021 | 300305 | Nanga Parbat | 0.029 | no |
2021 | 339789 | Welcome to the Moon | 0.028 | no |
2021 | 316343 | Capital Lux 2: Pocket | 0.028 | no |
2021 | 328286 | Mission ISS | 0.027 | no |
2021 | 308119 | Pax Renaissance: 2nd Edition | 0.027 | no |
2022 | 251661 | Oathsworn: Into the Deepwood | 0.026 | no |
2021 | 298383 | Golem | 0.026 | no |
2021 | 331685 | Hit the Silk! | 0.026 | no |
2021 | 249277 | Brazil: Imperial | 0.025 | no |
2022 | 338067 | 6: Siege – The Board Game | 0.025 | no |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.025 | no |
2021 | 315937 | X-Men: Mutant Insurrection | 0.024 | no |
2021 | 336794 | Galaxy Trucker | 0.024 | no |
2021 | 283242 | The Whatnot Cabinet | 0.024 | no |
2021 | 311920 | Ultimate Werewolf: Extreme | 0.023 | no |
2021 | 291859 | Riftforce | 0.022 | yes |
2021 | 320960 | Roll In One | 0.021 | no |
2021 | 331635 | Kameloot | 0.021 | no |
2022 | 331398 | Mythic Battles: Ragnarök | 0.020 | no |
2021 | 313730 | Harsh Shadows | 0.020 | no |
2021 | 290236 | Canvas | 0.020 | no |
2021 | 336382 | Marvel United: X-Men | 0.020 | no |
2021 | 259962 | Stress Botics | 0.020 | no |
2021 | 304783 | Hadrian's Wall | 0.019 | no |
2022 | 310873 | Carnegie | 0.019 | no |
2021 | 300523 | Biblios: Quill and Parchment | 0.019 | no |
2021 | 342942 | Ark Nova | 0.019 | no |
2022 | 273814 | Deliverance | 0.018 | no |
2021 | 283387 | Rocketmen | 0.017 | no |
2022 | 308028 | Drop Drive | 0.017 | no |
2022 | 332393 | Bridge City Poker | 0.017 | no |
2021 | 263222 | Shards of the Jaguar | 0.017 | no |
2021 | 339790 | Cocktail | 0.017 | no |
2021 | 340237 | Wonder Book | 0.016 | no |
2021 | 319792 | Fly-A-Way | 0.016 | no |
2021 | 346553 | Heuschrecken Poker | 0.016 | no |
2021 | 344408 | Full Throttle! | 0.016 | no |
2021 | 316287 | Quest | 0.016 | no |
2021 | 337787 | Summer Camp | 0.016 | no |
2022 | 342900 | Earthborne Rangers | 0.015 | no |
2022 | 326945 | Castles of Mad King Ludwig: Collector's Edition | 0.015 | no |
2021 | 338980 | Eastern Empires | 0.015 | no |
2021 | 298378 | Maharaja | 0.015 | no |
2023 | 312959 | Rallyman: DIRT | 0.015 | no |
2021 | 332290 | Stardew Valley: The Board Game | 0.015 | no |
2022 | 323707 | MOB: Big Apple | 0.014 | no |
2021 | 322708 | Descent: Legends of the Dark | 0.014 | no |
2021 | 340909 | Gloomholdin' | 0.014 | no |
2022 | 299106 | Fractal: Beyond the Void | 0.013 | no |
2021 | 334782 | Bayou Bash | 0.013 | no |
2021 | 299255 | Vienna Connection | 0.013 | no |
2021 | 325348 | Successors (Fourth Edition) | 0.013 | no |
2021 | 345976 | System Gateway (fan expansion for Android: Netrunner) | 0.012 | no |
2021 | 304333 | Zoollywood | 0.012 | no |
2021 | 343562 | Horrified: American Monsters | 0.012 | no |
2021 | 304324 | Dive | 0.012 | no |
2021 | 302510 | Mining Colony | 0.012 | no |
2021 | 329962 | Cantaloop: Book 2 – A Hack of a Plan | 0.012 | no |
2021 | 343847 | Dustbiters | 0.012 | no |
2022 | 304051 | Creature Comforts | 0.012 | no |
2022 | 347703 | First Rat | 0.012 | no |
2021 | 304985 | Dark Ages: Holy Roman Empire | 0.012 | no |
2021 | 295535 | Dark Ages: Heritage of Charlemagne | 0.012 | no |
2021 | 318184 | Imperium: Classics | 0.012 | no |
2022 | 340672 | Council of 12 | 0.011 | no |
2021 | 314491 | Meadow | 0.011 | no |
2021 | 339484 | Savannah Park | 0.011 | no |
2022 | 190572 | 1941: Race to Moscow | 0.011 | no |
2022 | 305096 | Endless Winter: Paleoamericans | 0.011 | no |